Preview processing and automatic correction of bulk data for software as a service applications

Abstract

The present invention may include a method for automatic correction and migration of a plurality of bulk data. The method may identify sources, where the sources include the plurality of bulk data. The method may identify a subset of the bulk data, where the subset represents one or more records selected from the plurality of bulk data. The method may upload the subset to an enterprise application. The method may determine an error list from the enterprise application based on the uploaded subset. The method may roll back the subset from the enterprise application and based on the determined error list, the method may match one or more rules to a one or more errors in the error list.

What is claimed is: 
     
       1. A processor-implemented method for automatic correction and migration of a plurality of bulk data, the method comprising:
 identifying one or more sources, wherein the one or more sources include the plurality of bulk data; 
 identifying a subset of the bulk data, wherein the subset is identified by combining a number of randomly selected records from each one of the identified one or more sources, and wherein the number of randomly selected records from each one of the identified one or more sources is proportional to a size of each of the identified one or more sources; 
 uploading the subset to an enterprise application; 
 determining an error list from the enterprise application based on the uploaded subset; 
 in response to an error being on the error list, removing the subset from the enterprise application; 
 matching one or more rules to one or more errors in the error list based on the determined error list and a plurality rule data; and 
 converting the subset using the matched one or more rules. 
 
     
     
       2. The method of  claim 1 , further comprising:
 based on matching the one or more rules to the one or more errors in the error list, displaying the one or more rules and a corresponding to each rule the one or more errors in the error list to a user; 
 allowing the user to change the one or more rules; and 
 in response to the user making a change to the one or more rules, updating a rule data with the changed one or more rules, wherein the rule data stores all the rules for the bulk data conversion to the enterprise application. 
 
     
     
       3. The method of  claim 2 , wherein the rule data comprising:
 an error number; 
 an error description, wherein the error description corresponds to the error number; and 
 the one or more rules corresponding to the error number. 
 
     
     
       4. The method of  claim 1 , further comprising:
 applying the matched rules to convert the bulk data into a compatible data, wherein the compatible data is in a format compatible to the enterprise application; and 
 uploading the compatible data to the enterprise application. 
 
     
     
       5. The method of  claim 1 , wherein identifying a subset of the bulk data is based on randomly selecting one or more records from the bulk data, wherein the selected one or more records are based on a size of each one of the identified sources. 
     
     
       6. The method of  claim 1 , wherein the one or more records selected from the plurality of the bulk data are selected randomly based on a size of the bulk data. 
     
     
       7. The method of  claim 1 , wherein matching one or more rules to one or more errors in the error list is performed by a probability value, wherein the probability value is determined based on matching one or more words from the one or more rules to one or more words of the one or more errors in the error list. 
     
     
       8. A computer system for automatic correction and migration of a plurality of bulk data, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising;
 identifying one or more sources, wherein the one or more sources include the plurality of bulk data; 
 identifying a subset of the bulk data, wherein the subset is identified by combining a number of randomly selected records from each one of the identified one or more sources, and wherein the number of randomly selected records from each one of the identified one or more sources is proportional to a size of each of the identified one or more sources; 
 uploading the subset to an enterprise application; 
 determining an error list from the enterprise application based on the uploaded subset; 
 in response to an error being on the error list, removing the subset from the enterprise application; 
 matching one or more rules to one or more errors in the error list based on the determined error list and a plurality rule data; and converting the subset using the matched one or more rules. 
 
     
     
       9. The computer system of  claim 8 , further comprising:
 based on matching the one or more rules to the one or more errors in the error list, displaying the one or more rules and a corresponding to each rule the one or more errors in the error list to a user; 
 allowing the user to change the one or more rules; and 
 in response to the user making a change to the one or more rules, updating a rule data with the changed one or more rules, wherein the rule data stores all the rules for the bulk data conversion to the enterprise application. 
 
     
     
       10. The computer system of  claim 9 , wherein the rule data comprising:
 an error number; 
 an error description, wherein the error description corresponds to the error number; and 
 the one or more rules corresponding to the error number. 
 
     
     
       11. The computer system of  claim 8 , further comprising:
 applying the matched rules to convert the bulk data into a compatible data, wherein the compatible data is in a format compatible to the enterprise application; and 
 uploading the compatible data to the enterprise application. 
 
     
     
       12. The computer system of  claim 8 , wherein identifying a subset of the bulk data is based on randomly selecting one or more records from the bulk data, wherein the selected one or more records are based on a size of each one of the identified sources. 
     
     
       13. The computer system of  claim 8 , wherein the one or more records selected from the plurality of the bulk data are selected randomly based on a size of the bulk data. 
     
     
       14. The computer system of  claim 8 , wherein matching one or more rules to one or more errors in the error list is performed by a probability value, wherein the probability value is determined based on matching one or more words from the one or more rules to one or more words of the one or more errors in the error list. 
     
     
       15. A computer program product for automatic correction and migration of a plurality of bulk data, the computer program product comprising:
 one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor, the program instructions comprising: 
 program instructions to identify one or more sources, wherein the one or more sources include the plurality of bulk data; program instructions to identify a subset of the bulk data, wherein the subset is identified by program instructions to combine a number of randomly selected records from each one of the identified one or more sources, and wherein the number of randomly selected records from each one of the identified one or more sources is proportional to a size of each of the identified one or more sources; 
 program instructions to upload the subset to an enterprise application; 
 program instructions to determine an error list from the enterprise application based on the uploaded subset; 
 in response to an error being on the error list, program instructions to remove the subset from the enterprise application; and 
 program instructions to match one or more rules to one or more errors in the error list based on the determined error list and a plurality rule data. 
 
     
     
       16. The computer program product of  claim 15 , further comprising:
 based on matching the one or more rules to the one or more errors in the error list, program instructions to display the one or more rules and a corresponding to each rule the one or more errors in the error list to a user; 
 program instructions to allow the user to change the one or more rules; and 
 in response to the user making a change to the one or more rules, program instructions to update a rule data with the changed one or more rules, wherein the rule data stores all the rules for the bulk data conversion to the enterprise application. 
 
     
     
       17. The computer program product of  claim 16 , wherein the rule data comprising:
 an error number; 
 an error description, wherein the error description corresponds to the error number; and 
 the one or more rules corresponding to the error number. 
 
     
     
       18. The computer program product of  claim 15 , further comprising:
 program instructions to apply the matched rules to convert the bulk data into a compatible data, wherein the compatible data is in a format compatible to the enterprise application; and 
 program instructions to upload the compatible data to the enterprise application. 
 
     
     
       19. The computer program product of  claim 15 , wherein program instructions to identify a subset of the bulk data is based on randomly selecting one or more records from the bulk data, wherein the selected one or more records are based on a size of each one of the identified sources. 
     
     
       20. The computer program product of  claim 15 , wherein the one or more records selected from the plurality of the bulk data are selected randomly based on a size of the bulk data.